99 results about "Constant false alarm rate" patented technology

The invention belongs to the technical field of wireless sensing and artificial intelligence, and discloses a high-robustness non-contact accurate electrocardiogram monitoring method based on a millimeter wave radar. Firstly, the distance and angle of a potential target are obtained through distance fast Fourier transform and digital beam forming technologies, and static background removal and thoracic cavity position detection are achieved in combination with mean filtering and a two-dimensional constant false alarm rate algorithm. And then a continuous phase is extracted by using a differential cross multiplication method, a two-step heartbeat-related phase extraction scheme is designed, body micro-motion and breathing interference are removed by adopting B-spline fitting and differential operation respectively, and a stable heartbeat-related phase signal is obtained. A heart rate-guided adaptive wavelet decomposition method is designed to obtain multiband features, and time-frequency joint features are extracted through a double-branch attention mechanism and a gating fusion part. Finally, the time-frequency joint features are input into an electrocardiosignal time domain reconstruction module based on a TransUNet architecture, high-quality reconstruction of electrocardiosignals is achieved, and the method has the advantages of being non-contact, continuous and convenient.

A non-contact real-time monitoring system of physiological signs based on millimeter-wave radar includes a millimeter-wave radar and multiple modules for processing radar signals. The millimeter-wave radar is configured to continuously transmit electromagnetic wave signals and simultaneously receive echo signals, perform frequency mixing processing on the echo signals to obtain an intermediate frequency signal, and process the intermediate frequency signal to obtain a radar four-dimensional data matrix. Human body physiological signs are monitored by analyzing body thoracic cavity micro-motion information in signals through the modules; a target echo is processed by adopting a constant false alarm rate detection algorithm, and invalid signals are filtered. A self-adaptive range cell selection algorithm based on short-time stability of respiratory signals is adopted to capture radar echoes reflecting physiological movement. Mixed human body physiological sign signals are processed by using a VMD algorithm, and key parameters in VMD are optimized by using a GWO algorithm.

The invention relates to the technical field of urban low-altitude safety monitoring, and discloses a low-altitude economic airspace passive safety early warning method and system. The method comprises the following steps: collecting multi-modal observation data streams of a target at different moments; generating multi-modal frame data with a unified timestamp; establishing a spatial confidence distribution map; extracting fusion discrimination features; executing multi-channel small target detection; continuously tracking the preliminary target; and introducing a constant false alarm rate framework to set a dynamic confidence threshold to execute alarm judgment. Compared with the prior art, the technical problem that high-confidence all-weather passive monitoring cannot be realized in urban core areas with dense buildings, serious signal shielding and easy GPS failure due to dependence on single vision or radar information in the prior art is solved. According to the method, the space confidence distribution diagram and the dynamic constant false alarm mechanism based on the shielding diagram are constructed by fusing the multi-modal sensing data, so that the safety early warning of the low-altitude small aircraft is realized, and the passive safety guarantee capability of the low-altitude economic airspace is improved.

The invention discloses an active sonar target identification method based on message passing multi-hypothesis tracking, and belongs to the technical field of underwater target detection. The method comprises the following steps: firstly, processing single-cycle sonar data by using adaptive constant false alarm detection, obtaining observation points, and forming an effective observation set through hierarchical clustering; thirdly, extrapolating the existing target, calculating the association probability of the existing target and the current observation by adopting a message passing method, and generating a plurality of groups of association hypotheses; then, the target state is corrected through Kalman filtering, target rejection and new management are executed, and a high-probability hypothesis is reserved; and finally, estimating the motion speed based on the target multi-period position sequence, and distinguishing a static object from a suspicious motion target according to a speed threshold. Through the multi-hypothesis tracking and probability message passing mechanism, clutter interference and static target influence in a complex underwater environment are effectively overcome, and the stability of target tracking, the accuracy of speed estimation and the overall reliability of system identification are remarkably improved.

The invention relates to the technical field of intelligent sensors, in particular to an unmanned aerial vehicle track intelligent tracking method based on a millimeter-wave radar, which comprises the following steps: receiving echo signals collected by the front end of the millimeter-wave radar, carrying out constant false alarm rate detection and Doppler frequency shift extraction on the echo signals, generating an unmanned aerial vehicle target space coordinate set, and carrying out target tracking on the unmanned aerial vehicle. And mapping the target space coordinate set of the unmanned aerial vehicle to a three-dimensional Euclidean space. According to the method, a non-convex optimization objective function containing beam switching time cost and precision constraint is constructed, and mathematical optimal solution of radar beam resources is realized. The generated adaptive scheduling instruction is used for adjusting the pulse repetition frequency and the beam residence time, it is ensured that radar front-end parameters dynamically evolve along with the target state, overall centroid tracking is emphasized for rigid body formation so as to save resources, independent high-frequency refreshing is emphasized for discrete targets so as to ensure the precision, and the accuracy is improved. And the continuity and robustness of trajectory tracking of the unmanned aerial vehicle in a complex electromagnetic environment are improved.

The present disclosure provides a constant false alarm rate-based downhole casing nondestructive testing method, device and medium. The method can include: obtaining a detection threshold according to a preset false alarm probability and background noise power of a target pulsed eddy current array detection signal, wherein the false alarm probability refers to the probability that the detection system incorrectly determines the presence of a damaged target when a non-damaged target is present in the downhole casing; screening the target pulsed eddy current array detection signal based on the detection threshold to obtain a downhole casing damage detection result signal; and determining the position of the downhole casing damage according to the downhole casing damage detection result signal. Through this technical solution, the detection threshold can be dynamically adjusted, and the position of the downhole casing damage can be accurately located, thereby improving the efficiency and accuracy of downhole casing damage detection.

The invention discloses an anti-high dynamic Doppler low signal-to-noise ratio satellite signal blind detection method, which comprises the following steps of: performing frequency domain analysis on a delay correlation signal according to a signal symbol rate, and dividing a signal band and a noise band near the delay correlation signal to construct a detection quantity to perform constant false alarm rate (CFAR) detection; and finally, obtaining a final signal existence or disappearance result through time consistency judgment. According to the method disclosed by the invention, the analytic CFAR threshold and the state machine smoothing are combined, and the problem of detection failure in a low signal-to-noise ratio and high dynamic Doppler environment in the prior art is solved.

The application provides a hypersonic platform radar target detection method, device and electronic equipment, relates to the technical field of hypersonic radar target detection, and the method comprises the following steps: inputting a received first echo signal into a time domain echo signal model, converting the first echo signal from a first signal domain to a second signal domain by using the time domain echo signal model, and obtaining a second echo signal; filtering the second echo signal by using an optimal parameter filter, obtaining a filtered third echo signal, converting the third echo signal into a third signal domain, and obtaining a coherent accumulation result; determining whether a target is detected by using a constant false alarm rate detection based on the coherent accumulation result, and determining the distance of the target based on the position of a peak value in the accumulation result in the case that it is determined that the target is detected. The hypersonic platform radar target detection method, device and electronic equipment provided by the application can realize high-precision, high-efficiency and highly adaptable radar target detection.

The application provides a terrain awareness and warning system excessive descent rate warning constant false alarm rate detection method, comprising the following steps: step 1: calculating the no-alarm trajectory data of an airplane according to the flight parameters of the airplane; calculating the post-alarm trajectory data of the airplane; performing collision detection on the no-alarm flight trajectory and the post-alarm flight trajectory with a first-order Markov random terrain to determine whether a successful alarm or an unnecessary alarm is generated; step 2: using a Monte Carlo method to perform a large number of simulations, counting the successful alarm rate and the false alarm rate to generate an SOC curve, and selecting an optimal alarm threshold point; step 3: selecting a constant false alarm rate range according to the obtained optimal alarm threshold point; obtaining the relationship between the descent rate and the alarm height from the selected constant false alarm rate; and step 4: repeating step 3 to obtain an optimal constant false alarm rate. The application can effectively reduce the false alarm rate of the excessive descent rate mode alarm, increase the safe flight probability, and adapt to more flight conditions.

The invention relates to the technical field of millimeter wave radars, and discloses a millimeter wave signal reconstruction method and system for indoor monitoring and a storage medium. The method comprises the following steps: acquiring video frame data of a target object and original I / Q data acquired by a millimeter wave radar, extracting key feature data of the target object from the video frame data, and mapping the key feature data to a radar coordinate system to form human body prior information; preprocessing the original I / Q data to obtain an amplitude matrix and a phase matrix, performing normalization processing on the amplitude matrix based on a noise baseline, and combining with the phase matrix to generate radar echo data; establishing a prior drive mapping model based on the two modes, and performing enhancement processing on the radar echo data to obtain enhanced radar echo data; and a binary detection map is generated by applying constant false alarm rate detection, the target object is tracked by adopting Kalman filtering, the motion trail information of the target object is obtained, and the accuracy of indoor area target object detection is improved.

The application provides a radar target detection method, system, device and medium based on two-feature fusion, and belongs to the technical field of radar signal processing. The method comprises the following steps: constructing training data by using existing radar target detection data, extracting phase linearity based on a training data extraction process, and extracting the relative peak height of the Doppler spectrum by using a relative peak height extraction process; based on the phase linearity and the relative peak height, a linear dimension reduction method with compact distribution is used to obtain a fusion matrix of two features; reference distance unit data and to-be-detected distance unit data are obtained in real time, the phase linearity extraction process and the relative peak height extraction process are respectively performed, and the fusion matrix is used to generate fusion features; based on the fusion features, the parameters of a generalized extreme value distribution are estimated, a detection statistic is constructed, a preset false alarm probability is combined to calculate an adaptive threshold, the target is judged by comparing the detection statistic with the threshold, and the constant false alarm rate detection under clutter suppression is realized.

This invention relates to a method and apparatus for resolving velocity ambiguity based on constant frequency assistance. The method includes the following steps: a radar sequentially transmits a constant frequency band signal and a linear continuously modulated pulse train, and acquires the radar echo signal; both the constant frequency band echo signal and the sawtooth band echo signal are mixed to obtain a constant frequency band intermediate frequency signal and a sawtooth band intermediate frequency signal; the constant frequency band intermediate frequency signal is processed by a fast Fourier transform to obtain a target true velocity estimate; the sawtooth band intermediate frequency signal is sequentially processed by a two-dimensional fast Fourier transform, a two-dimensional constant false alarm rate (CFAR) processing, and a centroid condensation processing to obtain a target range velocity estimate; based on a velocity matching method using a Fourier rotation factor, the target true velocity estimate is matched with the target range velocity estimate to obtain the true velocity of all targets. This method not only resolves velocity ambiguity but also improves velocity accuracy, offering advantages such as high velocity measurement accuracy, high real-time performance, and simplicity.

A method and apparatus for radar sensing in a disaggregated radio access network. The apparatus includes interface circuitry to receive data from a radio unit and processing circuitry to perform radar sensing processing on the received data to determine at least one of range, velocity, or direction of at least one target in an environment. The radar sensing processing includes range processing, Doppler processing, two-dimensional range-Doppler periodogram processing, constant false alarm rate (CFAR) detection processing, angular resolution processing, and post processing. The data received from the radio unit is beam domain data obtained by receive beamforming, and the processing circuitry is configured to perform decompression processing for converting the beam domain data to antenna domain data and perform at least the angular resolution processing and the post processing on the antenna domain data. The processing circuitry may perform the decompression processing after the CFAR detection processing.

This invention discloses a Wilcoxon-GO nonparametric detection method for ship targets in SAR images based on a large-scale selection logic, belonging to the field of image detection technology. The steps of this invention include: first, setting a detection window, which includes a detection unit, a reference window composed of a leading edge window and a trailing edge window, and a protection region; then, using the detection window to traverse the SAR ship remote sensing image pixel by pixel, with each movement distance equal to the width of the detection unit; subsequently, calculating the mean ratio (MR) of the leading edge and trailing edge windows, and using a threshold to determine whether the clutter is uniform or non-uniform; then, selecting a reference window based on the determination result; for uniform clutter, selecting the entire reference window, and for non-uniform clutter, selecting the leading edge / trailing edge window with the larger mean and widening it by 1; finally, calculating the detection statistic. R Set detection threshold T ,according to R and T The relationship between the detection unit and the target is determined. This invention maintains an approximately constant false alarm rate in non-uniform backgrounds at clutter edges, significantly outperforming the excessive increase in false alarms observed with traditional Wilcoxon technology, thus greatly improving false alarm control capabilities.

The invention discloses a low-altitude dynamic fence monitoring method and system based on a train positioning protection level, which are used for solving the problem that a static fence is difficult to adapt to high-speed movement and positioning errors of a train. According to the system, through a vehicle-mounted high-completeness positioning unit, the train position and the protection level thereof are solved in real time by using an integrity monitoring algorithm, and the position uncertainty is quantified; the space-time dynamic ellipsoid electronic fence with the train as the center is constructed by combining the train speed, and the size of the space-time dynamic ellipsoid electronic fence stretches and retracts in real time along with the protection level and And the ground monitoring terminal maps the fence into a space-time mask, adaptively adjusts the constant false alarm rate threshold value of the radar and the focal length of the camera, expands the field of view and reduces the detection threshold when the positioning uncertainty is large, focuses the core area when the positioning is accurate, and realizes hierarchical response and accurate coverage. According to the invention, satellite positioning completeness parameters are introduced, so that a safety blind area caused by positioning drift is effectively eliminated, and the accuracy and timeliness of low-altitude intrusion monitoring along the railway are improved.

This invention discloses a constant false alarm rate (CFAR) detection system and method for small sea surface targets based on feature game theory, relating to the field of radar signal processing technology. The system and method provided by this invention can be used for small sea surface target detection. It includes: extracting potential high-dimensional nonlinear features from the radar received signal using a feature extractor module; transforming the target detection problem into a binary classification problem using a target detector module to obtain the probability prediction result of the target detection task; and using the output feature vector of the feature extractor module and the probability density function of the target detector module as the input of a sea state discriminator module; and training the sea state discriminator module based on feature game learning to obtain the label distribution for different sea state environments. Therefore, using the above method, the detection of small sea surface targets under time-varying sea states is achieved, improving the detection rate and reducing the false alarm rate, while also exhibiting strong robustness.

The invention provides a medium-high repetition frequency velocity measurement method and system based on a height-finding radar, and relates to the technical field of data processing and signal processing. According to the method, the target point track distance obtained through data processing is used as prior information, the number of target distance folding times is calculated, and the problem of range finding ambiguity caused by medium-high repetition frequency is solved; a medium-high repetition frequency mode is adopted for tracking speed measurement, and the problem that the low repetition frequency speed measurement range is small is solved; a multi-frequency mode is adopted, the prior information of the track speed of a target point is utilized, and corresponding pulse repetition frequency and emission frequency are calculated and selected, so that the blind speed problem is solved; the interference problem of ground clutter and meteorological clutter is solved by adopting multi-dimensional CFAR (Constant False Alarm Rate) processing and a method of narrowing a target search range through acquired priori information such as target point track distance and point track speed; a point track velocity measurement and Doppler velocity measurement combined processing method is adopted to solve the problem of velocity measurement resolution of monopulse radar.

This invention discloses a method and system for monitoring the breathing and heartbeat of multiple individuals based on FMCW radar, relating to the fields of next-generation information technology and smart healthcare. The key technical points of this invention include: combining a constant false alarm rate (CFAR) detection method with the maximum number of extreme points within the range-angle matrix to identify the number and location of targets within the radar monitoring area, extracting their phase information, then using a sparse optimization method to extract the breathing and heartbeat signals of the targets from the phase signals, and finally displaying the target's location and breathing / heartbeat information in real time on the system interface. This invention overcomes the limitation of previous methods that could only detect a single person, effectively monitoring the breathing and heartbeat information of multiple individuals, and the system is easy to operate, demonstrating strong innovation and competitiveness.

The application discloses a kind of unmanned aerial vehicle spectrum anomaly detection and trajectory generation method based on unsupervised learning, including by SDR continuous acquisition broadband radio frequency signal, obtain IQ data stream;Short-time Fourier transform is carried out, and time-frequency spectrogram is obtained;Robust normalization processing is carried out to time-frequency spectrogram, and after inhibiting slow change drift, standardization spectrogram is obtained;Constant false alarm rate detection is executed, and preliminary anomaly candidate binary mask is generated;From standardization spectrogram, the spectrogram sub-block corresponding to preliminary anomaly candidate binary mask is identified, input into pre-trained unsupervised deep learning model, and abnormal score chart is obtained;With preliminary anomaly candidate binary mask is fused, and generates abnormal heat map;Abnormal heat map is clustered in time-frequency dimension, and trajectory correlation and filtering are carried out to clustering cluster across time window, and the time-frequency trajectory of unmanned aerial vehicle signal is output.The application enhances the reliability of anomaly detection, reduces the risk of false detection and missed detection, and guarantees the continuity and accuracy of trajectory generation.

The application discloses a target detection method, device and related equipment, which can be applied to a target detection system with at least two transmitting and receiving channels. The method comprises the following steps: obtaining a Doppler FFT result; pre-processing the Doppler FFT result to obtain a two-dimensional range-angle data spectrum; and performing two-dimensional constant false alarm rate (2D-CFAR) detection on the two-dimensional range-angle data spectrum to obtain target information. The two-dimensional constant false alarm rate detection is performed on the two-dimensional range-angle data spectrum obtained based on the Doppler FFT result, so that the detection performance can be ensured, the low-complexity constant false alarm rate detection operation can be realized, and the target detection performance is improved.

The application discloses a polarimetric SAR ship detection method based on fusion of statistics of Wasserstein distance, and relates to the field of polarimetric synthetic aperture radar ship target detection and identification. The method comprises the following steps: S1, acquiring polarimetric synthetic aperture radar data of an original ship and performing filtering processing; S2, performing feature extraction on the polarimetric synthetic aperture radar data after filtering processing to obtain three polarization features; S3, calculating a statistics map of Wasserstein distance of each pixel of a to-be-detected image by using the three polarization features; S4, screening a sea surface background on the statistics map by using a feature prior method, estimating a sea surface background distribution by using a kernel density method combined with a constant false alarm rate detection method, obtaining a threshold according to a preset false alarm rate, and completing pixel-by-pixel judgment on the sea surface background. The application significantly enhances the target / background contrast, and can still achieve high recall, low missed detection and good robustness in complex scenes such as strong sidelobes, strip artifacts and dense targets.

The application discloses a method for suppressing range ambiguity clutter of an end-on array airborne early warning radar based on subarray synthesis. Firstly, echo signals are subarray synthesized along horizontal rows of an end-on array to form one column of spatial channel data, and then the column of spatial channel data is subarray synthesized along horizontal columns to form one row of spatial channel data, so as to form a cross-shaped horizontal spatial synthesis channel data. Then, the obtained horizontal spatial synthesis channel data is subjected to clutter suppression processing by using a STAP method, so as to effectively filter out the clutter of the end-on array airborne early warning radar. Finally, the data subjected to the STAP processing is subjected to constant false alarm rate (CFAR) detection, so as to realize detection of a moving target. The scheme is suitable for clutter suppression processing of the end-on array airborne early warning radar and has the characteristics of less training sample requirement and low operation complexity.

The invention discloses a switching power supply peak signal detection method based on improved CFAR, and belongs to the technical field of signal processing and power electronics. The method comprises the following steps: controlling superposition of high-frequency ripples and noise through a dynamic random switching sequence, generating a transient peak in combination with a Gaussian pulse model, and synthesizing a high-trueness interference signal; designing a band-pass filter and a cross-correlation alignment algorithm to realize signal preprocessing and time domain alignment; multi-dimensional similarity evaluation indexes (a time domain correlation coefficient, dynamic time warping and spectrum energy similarity) are proposed to quantize signal features; an improved CFAR (Constant False Alarm Rate) detection algorithm is combined with a clustering matching strategy, and the detection precision and robustness of the transient peak are improved. The method can be applied to interference simulation, fault diagnosis and signal quality evaluation of power electronic equipment, and has the advantages of high-fidelity signal generation and low false alarm rate detection.

The application discloses a full polarization SAR image ship detection method, comprising the following steps: S1, pre-processing a full polarization SAR image to obtain different types of scattering power and polarization wave anisotropy parameters of each pixel; S2, using the decomposed different scattering power and combining the polarization wave anisotropy parameters to construct a full polarization SAR image detector; S3, using a generalized gamma distribution to describe the statistical characteristics of the full polarization SAR image detector to realize constant false alarm rate adaptive detection of the full polarization SAR image detector. The scattering characteristics and anisotropy of the scattering wave of the ship target are used to fully represent the ship target, so that the ship is strengthened and the background is weakened, and the ship can be detected from the complex marine background.

The application discloses a target detection method, a processing chip, an electronic device and a storage medium, and belongs to the computer field. The method comprises the following steps: acquiring environment data of a vehicle-mounted millimeter wave radar; determining a target index value of a to-be-detected unit in a range-Doppler matrix based on the environment data; determining a target weight value of a reference unit in the range-Doppler matrix based on the target index value, the reference unit being located around the to-be-detected unit, and the target weight value changing with the change of the target index value; and performing target detection by using a target constant false alarm rate detection algorithm based on the target weight value.

The application discloses a simulation processing method and device of a radar signal and electronic equipment. The method comprises the following steps: obtaining a radar echo signal generated by field programmable gate array in signal transceiving characteristic simulation of a radar signal; performing signal pulse compression processing on the radar echo signal to obtain a pulse modulation signal; performing multi-pulse cancellation and moving target detection processing on the pulse modulation signal to obtain a pulse matrix; performing constant false alarm rate detection on the pulse matrix in a thread synchronization mode to obtain an echo detection result; in the case that the echo detection result indicates that a radar detection target is detected, acquiring distance, speed and angle data of the radar detection target; and sending the distance, speed and angle data of the radar detection target to a central processor, so that the central processor determines track information of the radar detection target according to the distance, speed and angle data. The scheme provided in the application embodiment can improve the real-time performance of radar seeker simulation.

This invention discloses an on-chip spectrum sensing automatic gain control method and system for FPGA. The method includes: performing spectrum analysis on the received baseband signal, dynamically adjusting the detection threshold using a unit average constant false alarm rate algorithm, and calculating the minimum signal-to-noise ratio (SNR) required for signal detection based on the detection threshold; performing amplitude detection, logarithmic conversion, and filtering on the baseband signal based on the minimum SNR, and generating an attenuation control signal output to a digital attenuator at the RF front end to adjust the signal gain; wherein, the minimum SNR is dynamically updated based on the gain-adjusted baseband signal, and the attenuation is adjusted in real time based on the updated minimum SNR to stabilize the power of the input signal within the optimal dynamic range required for signal detection, forming a closed-loop feedback control.

This invention proposes a range estimation method for skywave over-the-horizon radar based on a sparse Bayesian algorithm. The implementation steps are as follows: beamforming is performed on the data received by the skywave over-the-horizon radar antenna array; pulse compression and moving target detection are performed on the echo data from the target's azimuth to obtain the range-Doppler matrix; two-dimensional constant false alarm rate (CFAR) detection is performed on the range-Doppler matrix; and the target's range information is obtained by sparse recovery of the echo data from the Doppler channel using the sparse Bayesian algorithm. This invention can improve the range resolution and range estimation accuracy of skywave over-the-horizon radar; it reduces the computational load and system complexity of the algorithm, making it more suitable for engineering applications.

A near-fuse ranging method based on fast warping Fourier transform, comprising the following steps: a single-chip radar in a near-fuse emits a triangular wave detection signal to a detection area, the signal is received by a receiving antenna of the single-chip radar after being reflected by the detection area, a radar echo digital signal is obtained by a pre-processing of a receiver front end of the single-chip radar, and the echo digital signal is sent to a signal processor; the echo digital signal is fitted by a WFFT fitting non-uniform filter group of the signal processor, and a modulus value of a processing result is taken to obtain a spectrum diagram of target energy accumulation with high resolution in a low frequency area and diffusion in a high frequency area; a detection threshold is set, a constant false alarm rate detection is performed on the spectrum diagram of target energy accumulation with high resolution in the low frequency area and diffusion in the high frequency area, and target frequency information is extracted; and distance information is calculated and transmitted to a fuse control system through a missile-borne computer. The present application improves the signal-to-noise ratio in the high frequency area and more accurately captures high frequency information.

This invention belongs to the field of electronic search technology and relates to a radio reconnaissance method and system based on multi-channel parallel processing and intelligent clustering. The method includes: performing polyphase filtering and digital channelization processing on broadband radio signals to obtain adjacent and overlapping channel sequences; performing square-law detection and constant false alarm rate detection on each channel sequence to generate initial pulse descriptors; establishing candidate correspondences within adjacent channels based on similarity of arrival time and noise consistency, and determining cross-channel merging relationships based on frequency range continuity and frequency-time relationship slope consistency to generate complete pulse descriptors; performing hierarchical clustering and sorting based on angle of arrival and pulse width; and performing multi-level differential analysis on the clustering results to extract repetition frequency sequences and determine repetition frequency types. The technical solution of this application can maintain the stability and consistency of cross-channel pulse merging and sorting results under broadband and high-density conditions, and improve the accuracy of radio search processing in complex electromagnetic environments.